Summary/Abstract

Canine distemper is an important infectious disease that affects many mammal species. There is evidence of CDV infection in all terrestrial carnivores families and some marine carnivore families. CDV has been detected in wild animal species such as the African lion and Amur tigers and has been responsible for substantial population declines of the animals during outbreaks. First seen in domestic dogs in the late 1970’s, CDV spread through the population rapidly (???). CDV is seen most commonly in domestic cats and dogs but frequent cross species transmission does occur in non-domestic carnivores. In domestic ferrets mortality rates can reach 100%. CDV has been responsible for population declines of endangered mustelids like the black-footed ferret. CDV is also endemic in the eastern U.S. raccoon population. Raccoons are thought to be a reservoir for other wild animals and domestic dogs as well as other species of carnivores. CDV has been found to be persisting in areas like Yellow Stone national park, which has a diverse carnivore population. Multiple outbreaks have occurred in the wolf, coyote and cougar populations Although raccoons are thought to be a major reservoir for CDV, little research has been done to identify the disease dynamics within this population.

Introduction

Canine distemper is an important infectious disease that affects many mammal species. The causative agent, canine distemper virus (CDV) is an enveloped, single stranded, negative sense RNA virus in the Morbillivirus family. Transmitted via the respiratory route, CDV is highly infectious (Deem, Spelman, Yates, & Montali, 2000). There is evidence of CDV infection in all terrestrial carnivores families and some marine carnivore families (Deem et al., 2000). Morbidity and mortality varies depending on the species but closely resembles rabies in wild carnivores (Hoff, Bigler, Proctor, & Stallings, 1974). The Mustelidae family is among the species with the highest fatality rate, while the domestic dog can be a asymptomatic carrier (Deem et al., 2000). CDV has been detected in wild animal species such as the African lion and Amur tigers and has been responsible for substantial population declines of the animals during outbreaks (Roelke-Parker et al., 1996; Seimon et al., 2013).

Canine Distemper Virus In the U.S.

First seen in domestic dogs in the late 1970’s, CDV spread through the population rapidly (Alison et al 2013). CDV is seen most commonly in domestic cats and dogs but frequent cross species transmission does occur in non-domestic carnivores (Allison et al 2013 and (Greene & Appel, 1990). Severity in domestic dogs depends on the animals’ immune status and age in addition to strain virulence (Beineke, Baumgärtner, & Wohlsein, 2015). In the U.S. raccoons (Procyon lotor), foxes (Vulpes vulpes and Urocyon cinereoargenteus), coyotes (Canis latrans), wolves (Canis lupus) , skunks (Mephitis mephitis), badgers (Taxidea taxus), mink (Mustela vison) and ferrets (mustelidae spp.) are among the species susceptible to CDV infection (???; Kapil et al., 2008). In domestic ferrets mortality rates can reach 100%. CDV has been responsible for population declines of endangered mustelids like the black-footed ferret. CDV is also endemic in the eastern U.S. raccoon population. Raccoons are thought to be a reservoir for other wild animals and domestic dogs as well as other species of carnivores (Alison et al 2013, and (Roscoe, 1993). CDV has been found to be persisting in areas like Yellow Stone national park, which has a diverse carnivore population. Multiple outbreaks have occurred in the wolf, coyote and cougar populations (Almberg, Cross, & Smith, 2010; Almberg, Mech, Smith, Sheldon, & Crabtree, 2009). Although raccoons are thought to be a major reservoir for CDV, little research has been done to identify the disease dynamics within this population. Available data is sparse, dated and focuses on individual states and discrete sites. The use of past and current presence only cases allows for spatio-temporal analysis of the CDV in the southeastern United States. The objective of this study was to identify spatial and temporal patters in distemper virus cases reported to the Southeastern Cooperative Wildlife Disease Study from 1975 to 2013.

Description of data and data source

Data was recorded from Canine distemper positive cases submitted to the Southeastern Cooperative Wildlife Disease Study between 1975 and 2013. Cases were identified as CDV by fluorescent antibody testing and/or histologic diagnosis of characteristic lesions. Species, date of submission, county of origin, and sex were noted. A total number of 701 positive cases were submitted from 13 states over the 38-year period. Positive cases were comprised of raccoons (n=462), gray foxes (n=211), striped skunks (n=13), coyotes (n=7), red foxes (n=3), gray wolves (n=3), one mink and a black bear.

Also census and county land area data from census.gov

Species frequency Table
Species n
Black Bear 1
Coyote 7
Gray Fox 211
Gray wolf 3
Mink 1
Raccoon 462
Red Fox 3
Striped Skunk 13

Questions/Hypotheses to be addressed

1.Are there temporal trends in cases diagnosed related to the ecology of the hosts?

2.Are there patterns in the timing of species being diagnosed suggesting cross species infection? (raccoons are considered primary reservoirs, are peaks in raccoon infection followed by other species peaks suggesting spillover)

3.Are there spatial patterns of infection within the southeast relating to landuse?

Methods

Data aquisition

Data of animals brought to SCWDS between 1975 and 2013, which were diagnosed as having CDV at post mortem. Cases were identified as CDV by fluorescent antibody testing and/or histologic diagnosis of characteristic lesions. Species, date of submission, county of origin, and sex were noted. ##Overview of Data Data contained the the follwing varibles….

Data import and cleaning

Detailed description of data analysis and cleaning in supplemtary folder

Time Series analsys

time series analysis and ARIMA model construction was conducted using the “fpp2” package from Forecating: principles and practice, Hyndman & Athanasopoulos.(Hyndman & Athanasopoulos, 2018)

Results

Univariate analysis

Initial probing of the data set revealed the vast majority of cases to be submitted from the state of Georgia. This is understandable as SCWDS is located in Athens, GA. The other feature is that almost all of the submitted cases are Raccoons or Gray Foxes. From this point the data analysis will focus on the state of Georgia and on these two species, Raccoon and Gray Fox. ###Initial Data Probing
Number of cases of CDV per state, submitted to SCWDS, 1075-2013

Number of cases of CDV per state, submitted to SCWDS, 1075-2013

Map of CDV cases per state submitted to SCWDS, 1975-2013 .

Map of CDV cases per state submitted to SCWDS, 1975-2013 .

Number of CDV cases per species submitted to SCWDS, 1975-2013

Number of CDV cases per species submitted to SCWDS, 1975-2013

Cases per Year

Cases per Year

From this point, data exploration and analysis will focus only on Gray foxes and Raccoons in the state of Georgia as this compromises the majority of cases.
Bivariate analysis of Species and Age of CDV cases submitted to SCWDS, 1975-2013

Bivariate analysis of Species and Age of CDV cases submitted to SCWDS, 1975-2013

Bivariate analysis of Species and Sex of CDV cases submitted to SCWDS, 1975-2013

Bivariate analysis of Species and Sex of CDV cases submitted to SCWDS, 1975-2013

#```{r, resultfigure3, fig.cap= ‘Species Time’, echo=FALSE, warning=FALSE, message=FALSE}

#```

#```{r, resultfigure3, fig.cap= ‘Species Time’, echo=FALSe, warning=FALSE, message=FALSE}

#```

Use a combination of text/tables/figures to explore and describe your data. You should produce plots or tables or other summary quantities for most of your variables. You definitely need to do it for the important variables, i.e. if you have main exposure or outcome variables, those need to be explored. Depending on the total number of variables in your dataset, explore all or some of the others.

Bivariate analysis

Create plots or tables and compute simple statistics (e.g. t-tests, simple regression model with 1 predictor, etc.) to look for associations between your outcome(s) and each individual predictor variable

Species Time

Species Time

##Spatial Mapping of Georgia Data

County Presence over Time of CDV, from cases submitted to SCWDS, 1975-2013

Cases of CDV in Gray Foxes and Raccoons in Georgia counties, from cases submitted to SCWDS, 1975-2013

Ripley's K analysis of CDV cases in Raccoons and Gray Foxes in Georgia, from cases submitted to SCWDs, 1975-2013

Ripley’s K analysis of CDV cases in Raccoons and Gray Foxes in Georgia, from cases submitted to SCWDs, 1975-2013

Time series analysis

Predictive Model

Gray Fox Prediction General Model

Gray Fox Prediction General Model

Gray Fox Prediction Model

Gray Fox Prediction Model

Raccoon Prediction General Model

Raccoon Prediction General Model

Raccoon Prediction Model

Raccoon Prediction Model

The first model, which uses the number of Raccoon cases from the previous month along with the predictive error for Gray Fox cases from the previosu month to predict Gray Fox cases in the current month is the more accurate model.

Use one or several suitable statistical/machine learning methods to analyze your data and to produce meaningful figures, tables, etc. This might again be code that is best placed in one or several separate R scripts that need to be well documented. You can then load the results produced by this code

Discussion

Initial introduction of CDV into wild carnivores in the U.S. in 1960’s was through grey foxes and subsequent spread to raccoons. (Hoff et al., 1974). Outbreak in Raccoons in Berlin, Germany appears to have originated in foxes with transmission seeming to readily occur between the species. (???)

The analysis of the CDV case data in Raccoons and Gray Foxes suggests a relationship between cases in the two species, with the ARIMA model produced for Gray Fox cases suggesting that monthly case numbers in Gray Foxes can quite accurately be predicted using the previous months Gray Fox error data and the number of Raccoon cases from this month. A second model for the prediction of Raccoon cases using the previous months raccoon data in addition to Gray Fox cases from the previous three months was also quite accurate at predicting Raccoon cases, albeit it had a slightly higher error than the other model.

The spatial analysis of the data showed significant clustering of cases, which is in line with the ecology of the virus which tends to have epizootics where it spreads quickly amongst nearby susceptible. The primary mode of CDV infection is aerosol inhalation, suggesting habitat overlap and contact (Hoff et al., 1974). There appeared to be a much greater number of cases in the northern part of the state. Again the possible reasons for this are diverse; reporting bias due to a range of possible reasons; as the northern part of the state is more densely populated by humans, closer proximity to SCWDS, more suitable habitat and a consequently greater population of susceptible raccoons and gray foxes. Interestingly, there may be a parabolic relationship between population density and number of cases, with very high densities and very low densities having lower number of cases

The data suggests a correlation between breeding season and the number of cases reported, with positives more likely to occur during the breeding season. This could be due to a number of reasons; there may be more contact between individual animals as they search for mates promoting aerosol spread of virus . Contact structure of a raccoon population can significantly impact disease transmission with Raccoon contact networks being shown to change depending on the season (breeding vs. non breeding); Rabies has been shown to spread quickly in raccoons when introduced during the breeding season.) (Reynolds, Hirsch, Gehrt, & Craft, 2015). Other potential influences of the breeding season and cases aside from contact may be the phycological strain of reproduction may leave animals more susceptible to the virus or as these cases are from animals found dead it could be that the increased movement from the breeding season leads to more being killed in other ways, such as on roads, and they happen to also be CDV positive at necropsy.

There as significant limitations to using this data set to draw conclusions about CDV cases in wild animals in Georgia. This data set comes from passive surveillance only, with it being reliant on dead animals being found and sent to SCWDS by DNR officers for necropsy. This leaves the data open to significant influence by reporting bias, as the distribution of DNR officers is not uniform across the state. Passive surveillance is also only showing part of the picture, with the results being heavily skewed towards symptomatic cases. Gray foxes and raccoons in Tennessee (Nov. 2013 – Aug. 2014) were infected frequently, but passive surveillance only captures animals showing clinical signs. Does not account for asymptomatic cases with 55% of asymptomatic animals tested being positive in this study (Pope, Miller, Riley, Anis, & Wilkes, 2016).

Conclusions

What are the main take-home messages?

Include citations in your Rmd file using bibtex, the list of references will automatically be placed at the end

References

Almberg, E. S., Cross, P. C., & Smith, D. W. (2010). Persistence of canine distemper virus in the Greater Yellowstone Ecosystem’s carnivore community. Ecological Applications. https://doi.org/10.1890/09-1225.1

Almberg, E. S., Mech, L. D., Smith, D. W., Sheldon, J. W., & Crabtree, R. L. (2009). A serological survey of infectious disease in yellowstone national park’s canid community. PLoS ONE. https://doi.org/10.1371/journal.pone.0007042

Beineke, A., Baumgärtner, W., & Wohlsein, P. (2015). Cross-species transmission of canine distemper virus-an update. https://doi.org/10.1016/j.onehlt.2015.09.002

Deem, S. L., Spelman, L. H., Yates, R. A., & Montali, R. J. (2000). CANINE distemper in terrestrial carnivores: A review. Journal of Zoo and Wildlife Medicine. https://doi.org/10.1638/1042-7260(2000)031[0441:cditca]2.0.co;2

Greene, C. E., & Appel, M. J. G. (1990). Canine distemper (pp. 226–241).

Hoff, G. L., Bigler, W. J., Proctor, S. J., & Stallings, L. P. (1974). Epizootic of canine distemper virus infection among urban raccoons and gray foxes. Journal of Wildlife Diseases. https://doi.org/10.7589/0090-3558-10.4.423

Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and practice. OTexts: Melbourne, Australia.

Kapil, S., Allison, R. W., Johnston, L., Murray, B. L., Holland, S., Meinkoth, J., & Johnson, B. (2008). Canine distemper virus strains circulating among north American dogs. Clinical and Vaccine Immunology. https://doi.org/10.1128/CVI.00005-08

Pope, J. P., Miller, D. L., Riley, M. C., Anis, E., & Wilkes, R. P. (2016). Characterization of a novel Canine distemper virus causing disease in wildlife. Journal of Veterinary Diagnostic Investigation. https://doi.org/10.1177/1040638716656025

Reynolds, J. J. H., Hirsch, B. T., Gehrt, S. D., & Craft, M. E. (2015). Raccoon contact networks predict seasonal susceptibility to rabies outbreaks and limitations of vaccination. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.12422

Roelke-Parker, M. E., Munson, L., Packer, C., Kock, R., Cleaveland, S., Carpenter, M., … Appel, M. J. G. (1996). A canine distemper virus epidemic in Serengeti lions (Panthera leo). Nature. https://doi.org/10.1038/379441a0

Roscoe, D. E. (1993). Epizootiology of canine distemper in New Jersey raccoons. Journal of Wildlife Diseases. https://doi.org/10.7589/0090-3558-29.3.390

Seimon, T. A., Miquelle, D. G., Chang, T. Y., Newton, A. L., Korotkova, I., Ivanchuk, G., … McAloose, D. (2013). Canine distemper virus: An emerging disease in wild endangered Amur tigers (Panthera tigris altaica). mBio. https://doi.org/10.1128/mBio.00410-13